Land Loss and Displaced Population of
the North Carolina Coast due to Predicted
Sea-Level Rise
Eric W. Hill
Environmental Science Program, Appalachian State University, Boone, NC
Abstract
The land loss and displaced population of the North Carolina coast caused by predicted sea-level rise are quantified. Maps are created to show land area that would
be inundated from four sea-level rise predictions. The predictions used are a sea-level
rise in the year 2100 of 1, 2, 4, and 7 feet above the 1990 level. The land area and displaced population are calculated for each of the predictions. The results show that
18.1 percent of the land area and 143,068 people of coastal North Carolina would be
inundated with a sea-level rise of 1 foot, 22.5 percent land area and 175,528 people
with 2 feet of rise, 27.6 percent land area and 215,280 people with 4 feet of rise, and
34.4 percent land area and 272,223 people with 7 feet of rise.
1.0 Introduction
Many scientists agree that climate change is one
of the most pressing world issues. Of the many
impacts that climate change has on the planet,
sea-level rise could be one of the most detrimental to humans. According to McGranahan et al.
[1], “2 percent of the world’s land area is less than
10 meters above sea level but contains 10 percent of the world’s population and 13 percent
of the world’s urban population.” Sea-level rise
would have impacts on society through coastal
erosion, increased susceptibility to storm surges,
and groundwater contamination [2]. In addition
to the impacts on humans, sea-level rise would
also cause changes to near-shore coastal dynamics, including sand abundance and distribution
and shipping channels.
Sea level is defined as the average height of
the sea with respect to a reference surface [3].
The sea level changes on a short-term basis due
to waves, tides, storms, and seasonal weather
patterns [4]. Long-term sea level change is dominated by fluctuations in global near-surface
air temperature and fresh water input from ice
sheets and glaciers. Of these contributing factors, ice sheets have the greatest ability to raise
the sea level. The complete melting of ice sheets
would raise the global sea level about 70 meters
[5]. Over the last century, the mean sea-level
rose 1 to 2 mm/year, with thermal expansion
caused by warming contributing 0.5 ± 0.2 mm
54
[2]. Thermal expansion is a change in the volume of ocean water in response to heat transfer
with the atmosphere. Because the mean global
surface temperature has increased 0.85°C from
1880-2012, there is a strong correlation between
temperature and sea-level [6]. This increase in
temperature has come as a result of the emission of greenhouse gases from human activities.
Another concern with regards to ice sheet and
glacier melting is soot. Soot is twice as effective
as carbon dioxide when it comes to altering the
global surface air temperature [7]. When deposited on snow and ice, soot decreases the average
albedo of the earth and increases the amount of
sunlight that is absorbed.
The coastal region of North Carolina is one
of the state’s most valuable resources.
The
beaches that line the Atlantic Ocean are popular vacation spots for people from around the
world. The Cape Hatteras National Seashore on
the Outer Banks of North Carolina received over
2.31 million visitors in 2013 (outerbanks.org). In
2012, the total revenue from tourism in coastal
counties was over $2.91 billion (NC Department
of Commerce, nccommerce.com). From the
2010 census, the total population of the coastal
counties was 988,911 (US Census Bureau, census.gov). In order to manage this region of the
state, the Coastal Area Management Act of 1974
was passed by the North Carolina General Assembly. This act created the Coastal Resources
Journal of Student Research in Environmental Science at Appalachian
Commission (CRC), which is a 13-member body
that provides management for the development
of land and protection of natural systems. Ensuring a balance between the two for the 20 coastal
counties that are adjacent to ocean waters is a
task of the CRC (NC Department of Coastal Management, ncdenr.org).
In 2012, the North Carolina General Assembly
passed House Bill 819. This legislation effectively
places a four year moratorium on the ability of
planners to use up-to-date science when creating plans for controlling the impacts of future
sea-level rise. Historical sea-level measurements
must be used to estimate the future sea-level
rise. This is controversial because it is known
that sea-level will increase at an exponential rate,
whereas historical sea-level trends are linear.
2.0 Methods and Data
The North Carolina counties that were focused
on were Beaufort, Bertie, Brunswick, Camden,
Carteret, Chowan, Craven, Currituck, Dare, Gates,
Hertford, Hyde, New Hanover, Onslow, Pamlico,
Pasquotank, Pender, Perquimans, Tyrrell, and
Washington (NC Department of Coastal Management, ncdenr.org). The location of these counties along with their population densities is displayed in Figure 1.
The county boundary and shoreline shapefiles were loaded into ArcMap (ArcGIS, ESRI, Redlands, CA). From the county boundary layer, the
counties that are subject to the rules and policies
of the Coastal Resource Commission were selected and a new layer was created (DCM, dcm2.enr.
state.nc.us/).
The LiDAR (Light Detection and Ranging;
http://oceanservice.noaa.gov/facts/lidar.html)
elevation grid for each county was then inserted
into the map. The layer properties were changed
so that transparency was 0%. The symbology
was changed to display classification of elevation based on the different sea-level rise predictions. Each color represents the land area that
would be inundated due to the sea-level rise
predictions. For example, 4 feet of sea-level rise
is displayed as the sum of the blue, yellow, and
Figure 1. Map of coastal counties with population density (people per sq mi).
Volume 4, 1st Edition • Spring 2014
55
orange colors (Figure 2).
The map displaying the North Carolina
coastline assuming the greatest amount of predicted sea-level rise was created by changing
the symbology of the elevation grid of each
county so that areas with an elevation of 0 to 7
feet are displayed in green and area with an elevation greater than 7 feet are displayed in tan.
The green boundary between green and blue
is effectively the current coastline. The county
boundary layer was changed to blue to simulate
the current bodies of water. Land area owned
by federal government agencies (Department of
Defense, Fish and Wildlife Service, Forest Service,
and National Park Service) is displayed in Figure
3. The municipal boundaries layer was added to
the map and eight significant municipalities are
selected. These municipalities were displayed
with a black dot and labeled on Figure 3.
To create Table 1, the attribute table of each
county’s elevation grid was exported to a text
file and opened in Microsoft Excel (Microsoft
Corporation, Redmond, Washington). The elevations lower than -1 feet were removed in order to
eliminate some of the error from the LiDAR data.
The ‘COUNT’ column represents the number of
cells in the raster dataset with the value in the
corresponding ‘VALUE’ column. For each sealevel rise scenario, the number of cells in the raster dataset less than that value was added. For
example, in the sea-level rise scenario of 2 feet,
everything less than or equal to 2 feet in elevation were summed. The percentage of the total
number of raster cells was calculated for each
sea-level rise scenario in each county. Next, the
total land area inundated with each sea-level rise
prediction was calculated. Because the elevation
data is stored in a 20-foot grid as described in the
Figure 2. Map of inundated land based on sea-level rise predictions of 1 foot, 2 feet, 4 feet, and 7 feet.
The 1 foot scenario is displayed in blue. The yellow color represents land that is between 1 and 2 feet
in elevation. Therefore, the 2 foot scenario would be shown as the sum of blue and yellow colors.
Following this same method, the 4 foot scenario is displayed as the sum of blue, yellow, and orange
colors. The 7 foot scenario is displayed as the sum of the blue, yellow, orange, and red colors.
56
Journal of Student Research in Environmental Science at Appalachian
Figure 3. Map of current North Carolina coast (green) and North Carolina coast assuming 7 feet of sealevel rise. Major population centers and land owned by the federal government are also displayed.
Table 1. Percent land area and total land area inundated for each coastal county based on 1990 to
2100 sea-level rise predictions.
Percent Land Area Inundated (%)
County
Beaufort
Bertie
Brunswick
Camden
Carteret
Chowan
Craven
Currituck
Dare
Gates
Hertford
Hyde
New Hanover
Onslow
Pamlico
Pasquotank
Pender
Perquimans
Tyrell
Washington
AVERAGE
TOTAL
1 ft
8.3
7.8
6.7
28.1
23.6
10.2
6.1
45.4
60.0
10.4
6.4
49.8
19.5
6.2
21.9
13.7
5.2
12.6
57.7
8.8
20.4
-
2 ft
11.3
8.7
8.0
30.5
32.2
11.4
7.2
50.8
75.1
11.3
7.1
65.5
23.8
7.0
28.4
17.3
7.1
13.7
72.3
11.5
25.0
-
4 ft
16.8
9.6
9.3
36.7
44.6
13.4
9.3
58.4
86.7
12.7
8.3
77.1
27.6
8.2
36.7
27.0
8.8
16.4
87.8
16.4
30.6
-
Volume 4, 1st Edition • Spring 2014
7 ft
26.4
11.1
11.0
54.4
63.0
17.3
13.4
74.7
94.8
14.7
10.1
86.3
31.6
9.7
50.6
44.0
11.0
27.7
94.1
25.4
38.6
-
Not Inundated
73.6
88.9
89.0
45.6
37.0
82.7
86.6
25.3
5.2
85.3
89.9
13.7
68.4
90.3
49.4
56.0
89.0
72.3
5.9
74.6
61.4
-
Total Land Area Inundated (sq mi)
1 ft
71
56
59
70
132
18
45
134
242
35
23
325
42
49
79
32
46
33
235
33
88
1,758
2 ft
97
62
70
76
180
20
53
150
303
38
25
428
52
55
103
40
63
36
294
43
109
2,189
4 ft
144
68
82
92
249
24
68
172
350
43
29
504
60
64
133
63
77
43
358
62
134
2,685
7 ft Not Inundated
226
629
79
635
97
782
136
114
352
207
31
147
98
634
220
75
383
21
50
291
36
320
564
90
69
149
76
706
183
179
103
131
96
783
72
188
383
24
96
281
167
319
3,349
6,384
57
file metadata, the number of cells could be multiplied by 400 feet to gain the land area inundated
from each prediction.
The number of affected people, as seen in
Table 2, was calculated. The total population
of each county was obtained from the 2010
United States Census. The population density
for each county was calculated by dividing the
total population by total land area. The affected
population for each sea-level rise scenario was
calculated by multiplying the population density
and the land area inundated for each scenario
calculated in Table 1.
Table 2. Displaced population for each coastal
county based on 1990 to 2100 sea-level rise
predictions.
County
1 ft
2 ft
4 ft
7 ft
Beaufort
3,943
5,406
8,045 12,624
Bertie
1,665
1,847
2,037
2,359
Brunswick
7,172
8,565 10,012 11,810
Camden
2,800
3,049
3,659
5,425
Carteret
15,654 21,394 29,649 41,876
Chowan
1,509
1,682
1,989
2,565
Craven
6,319
7,474
9,656 13,861
Currituck
10,697 11,961 13,751 17,586
Dare
20,346 25,471 29,397 32,160
Gates
1,265
1,375
1,550
1,798
Hertford
1,574
1,743
2,038
2,480
Hyde
2,891
3,804
4,480
5,013
New
39,605 48,228 55,877 63,982
Hanover
Onslow
11,038 12,503 14,500 17,187
Pamlico
2,872
3,727
4,818
6,654
Pasquotank 5,590
7,019 10,983 17,879
Pender
2,723
3,724
4,598
5,730
Perquimans 1,696
1,847
2,209
3,726
Tyrell
2,541
3,184
3,868
4,146
Washington 1,166
1,525
2,163
3,364
TOTAL
143,068 175,528 215,280 272,223
Not Inundated
35,135
18,923
95,621
4,555
24,593
12,228
89,644
5,961
1,760
10,399
22,189
797
138,685
160,585
6,490
22,782
46,487
9,727
261
9,864
716,688
3.0 Analysis and Discussion
The sea-level rise prediction scenarios used to
create Figure 1 were 1 foot, 2 feet, 4 feet, and 7
feet. These predictions are measured as sea-level
rise in year 2100 as measured from the mean sea
level in 1990. The 1 foot prediction is directly
from the IPCC report, which is considered a conservative estimate of sea-level rise by the end of
the century [8]. The other three predictions were
calculated by Vermeer and Rahmstorf using a
model based on changes in temperature using
IPCC emission scenarios [8]. From the model,
even the sea-level rise prediction from the lowest emission scenario was greater than the predictions given in the IPCC report.
The counties that would suffer the largest im58
pacts are those in the central and northern part
of the coastal region. Even with the most conservative sea-level rise prediction, Currituck, Dare,
Hyde, and Tyrell counties would still lose over 45
percent of their land area (Table 1). In total, 18.1
percent of the land area lies below 1 foot (Figure
4). The land area that lies between 1 and 7 feet
in elevation contributes 16.3 percent of the land
area (Figure 4).
In order to help analyze the impact of sealevel rise on the North Carolina Coast, a map
showing the possible new coastline as it relates
to major population centers and existing federal
lands was created (Figure 3). This map displays
the current coastline in green and the future
coastline in tan. The new coastline is assuming
7 feet of sea-level rise. Many of the major population centers will remain relatively safe. The
largest city in the area, Wilmington, would only
be affected on its outskirts. Other cities such as
Elizabeth City, Edenton, Morehead City, Washington, and New Bern may require substantial
effort to be protected from the encroaching sea.
The town of Kill Devil Hills and the rest of the outer banks will be reduced to a few small islands.
Another area to note is Marin Corps Base Camp
Lejeune, located just south of Jacksonville. This
area is located on relatively high ground and will
remain safe in the event of maximum sea-level
rise (Figure 3). Many National Parks, wildlife refuges, national forests, and other land owned by
the federal government would be lost if the sealevel were to rise 7 feet (Figure 3).
Most of the coastal counties of North Carolina have low population density. Over half of the
counties have a population density less than 70
people per square mile. The three counties with
the highest population densities are New Hanover County, Pasquotank County, and Onslow
County (Figure 1). These counties are home to
the three largest cities in the region: Wilmington,
Elizabeth City, and Jacksonville, respectively. Using the countywide population density to calculate the number of affected people proves to be
problematic. By definition, population density is
the average number of people living in a given
area of land. This assumes that the population is
evenly distributed throughout the county, which
is not true. For example, the majority of the population of New Hanover County lives in the city of
Wilmington, which is located in the center of the
county. New Hanover County does not lose that
much land compared to some of the other coun-
Journal of Student Research in Environmental Science at Appalachian
Figure 4. Percentage of land area inundated based on 1990 to 2100 sea-level rise predictions. [LEFT]
A 1 foot sea-level rise would result in 18.1 percent of land area to be inundated. Each of the other
sea-level rise scenario is displayed as the additional percentage of land area that would be inundated.
For example, a 2 foot se-level rise would result in an additional 4.4 percent or a total of 22.5 percent
of land area to be inundated and a 4 foot sea-level rise would result in an additional 5.1 percent of
a total of 27.6 percent of land area to be inundated; Population displaced by predicted sea level rise
[RIGHT]. For each sea-level rise scenario, the percentage of the total population is also displayed. A 1
foot sea-level rise would result in the displacement of 143068 people. Each of the other sea-level rise
predictions is displayed as the additional population affected.
ties; because of the high population density, it
has the highest displaced population (Table 2).
LiDAR data is very accurate when determining the elevation over dry land. However, bodies
of water have a negative effect on the accuracy
of LiDAR data [9]. The inherent nature of the
North Carolina coast means that there are possible inaccuracies with the LiDAR data used to
create the maps.
This study only used the current elevation to
determine the extent of sea-level rise. There are
many factors that could prove this type of analysis to be incorrect in the long run. The cities and
towns along the coast are bound to take steps
to protect their community, and there are many
coastal management strategies that have varying degrees of success [10]. Additionally, sediments along coastlines are always moving and
changing. The combination of waves and sealevel rise would cause the Outer Banks of North
Carolina to move towards the mainland, among
other effects [11]. These maps do not account
for this coastal sediment transport.
4.0 Conclusions
as well as near-shore coastal dynamics. The
causes of sea-level rise are well-known and are
associated with increasing temperatures (i.e. ice
sheet and glacier melting, thermal expansion).
However, the dynamics of how ice sheets and
glaciers move and change is an area of study that
requires more research. A better understanding
of ice sheet dynamics would increase the accuracy of sea-level rise predictions and climate
models used to predict the future conditions of
the earth. Additionally, developing more accurate estimates for displaced population due to
sea-level rise is essential in getting the public to
recognize the magnitude of this issue.
Because of the social and economic value of
the North Carolina coast, more resources need to
be allocated to study sea-level rise. This research
found that even the most conservative sea-level
rise prediction would have serious implications
to the State. Valuable real estate, natural habitats, and natural beauty are at risk of being submerged if the state government continues to
ignore modern science. Scientists, policy makers, and the public will need to work together to
create a plan that handles sea-level rise.
Sea-level rise has the potential of affecting a
large number of people and coastal economies,
Volume 4, 1st Edition • Spring 2014
59
Acknowledgments
The LiDAR, county boundary, and municipal
boundary data used to generate the maps can
be found on the NCDOT website. The shoreline
data can be found on the North Carolina Department of Environment and Natural Resources’
Division of Coastal Management website. The
2010 census data can be obtained from the United States Census Bureau.
Profile Response to sea level rise: a process-based approach, Earth Surface Processes and Landforms, 37(3), 354-362, doi:
10.1002/esp.2271.
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Journal of Student Research in Environmental Science at Appalachian
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